Causality-based Feature Selection: Methods and Evaluations

17 November 2019

Papers citing "Causality-based Feature Selection: Methods and Evaluations"

35 / 35 papers shown

Title
Knoop: Practical Enhancement of Knockoff with Over-Parameterization for Variable Selection Xiaochen Zhang Yunfeng Cai Haoyi Xiong 72 0 0 28 Jan 2025
Causal Learner: A Toolbox for Causal Structure and Markov Blanket Learning Zhaolong Ling Kui Yu Yiwen Zhang Lin Liu Jiuyong Li CML 43 28 0 11 Mar 2021
Causal query in observational data with hidden variables Debo Cheng Jiuyong Li Lin Liu Jixue Liu Kui Yu T. Le CML 28 11 0 28 Jan 2020
Causality for Machine Learning Bernhard Schölkopf CML AI4CE LRM 68 455 0 24 Nov 2019
Invariant Risk Minimization Martín Arjovsky Léon Bottou Ishaan Gulrajani David Lopez-Paz OOD 161 2,190 0 05 Jul 2019
D-VAE: A Variational Autoencoder for Directed Acyclic Graphs Muhan Zhang Shali Jiang Zhicheng Cui Roman Garnett Yixin Chen GNN BDL CML 62 199 0 24 Apr 2019
DAG-GNN: DAG Structure Learning with Graph Neural Networks Yue Yu Jie Chen Tian Gao Mo Yu BDL CML GNN 64 481 0 22 Apr 2019
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms Yoshua Bengio T. Deleu Nasim Rahaman Nan Rosemary Ke Sébastien Lachapelle O. Bilaniuk Anirudh Goyal C. Pal CML OOD 91 334 0 30 Jan 2019
Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness Raphael Suter Ðorðe Miladinovic Bernhard Schölkopf Stefan Bauer CML OOD DRL 103 160 0 31 Oct 2018
A Survey of Learning Causality with Data: Problems and Methods Ruocheng Guo Lu Cheng Jundong Li P. R. Hahn Huan Liu CML 54 169 0 25 Sep 2018
Bayesian Structure Learning by Recursive Bootstrap R. Y. Rohekar Yaniv Gurwicz Shami Nisimov G. Koren Gal Novik CML 110 17 0 13 Sep 2018
Constructing Deep Neural Networks by Bayesian Network Structure Learning R. Y. Rohekar Shami Nisimov Yaniv Gurwicz G. Koren Gal Novik BDL 95 26 0 24 Jun 2018
A Unified View of Causal and Non-causal Feature Selection Kui Yu Lin Liu Jiuyong Li CML 33 96 0 16 Feb 2018
Discovering Markov Blanket from Multiple interventional Datasets Kui Yu Lin Liu Jiuyong Li 42 6 0 25 Jan 2018
Causal Generative Neural Networks Olivier Goudet Diviyan Kalainathan Philippe Caillou Isabelle M Guyon David Lopez-Paz Michèle Sebag BDL CML DRL 48 59 0 24 Nov 2017
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions Sara Magliacane T. V. Ommen Tom Claassen Stephan Bongers Philip Versteeg Joris M. Mooij OOD CML 89 235 0 20 Jul 2017
Forward-Backward Selection with Early Dropping Giorgos Borboudakis Ioannis Tsamardinos 128 97 0 30 May 2017
Learning Identifiable Gaussian Bayesian Networks in Polynomial Time and Sample Complexity Asish Ghoshal Jean Honorio CML TPM 65 55 0 03 Mar 2017
Challenges of Feature Selection for Big Data Analytics Jundong Li Huan Liu 55 208 0 07 Nov 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 717 16,828 0 16 Feb 2016
Feature Selection: A Data Perspective Jundong Li Kewei Cheng Suhang Wang Fred Morstatter Robert P. Trevino Jiliang Tang Huan Liu 53 806 0 29 Jan 2016
Scalable and Accurate Online Feature Selection for Big Data Kui Yu Xindong Wu W. Ding J. Pei 65 152 0 30 Nov 2015
Margins of discrete Bayesian networks R. Evans 47 68 0 09 Jan 2015
Causal inference using invariant prediction: identification and confidence intervals J. Peters Peter Buhlmann N. Meinshausen OOD 96 961 0 06 Jan 2015
Theory Refinement on Bayesian Networks Wray Buntine BDL 63 786 0 20 Mar 2013
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data David Heckerman D. Geiger D. M. Chickering TPM 98 3,980 0 27 Feb 2013
Learning Equivalence Classes of Bayesian Networks Structures D. M. Chickering 84 831 0 13 Feb 2013
Large-Sample Learning of Bayesian Networks is NP-Hard D. M. Chickering Christopher Meek David Heckerman BDL 100 792 0 19 Oct 2012
Local Structure Discovery in Bayesian Networks Teppo Niinimaki P. Parviainen 65 43 0 16 Oct 2012
Inferring deterministic causal relations P. Daniušis Dominik Janzing Joris Mooij Jakob Zscheischler Bastian Steudel Kun Zhang Bernhard Schölkopf CML 67 191 0 15 Mar 2012
Identifiability of Causal Graphs using Functional Models J. Peters Joris Mooij Dominik Janzing Bernhard Schölkopf 84 154 0 14 Feb 2012
Kernel-based Conditional Independence Test and Application in Causal Discovery Kun Zhang J. Peters Dominik Janzing Bernhard Schölkopf BDL CML 82 618 0 14 Feb 2012
Learning high-dimensional directed acyclic graphs with latent and selection variables Diego Colombo Marloes H. Maathuis M. Kalisch Thomas S. Richardson CML 102 465 0 29 Apr 2011
Causal Inference on Discrete Data using Additive Noise Models J. Peters Dominik Janzing Bernhard Schölkopf CML 78 155 0 02 Nov 2009
Learning Bayesian Networks with the bnlearn R Package M. Scutari BDL 139 1,723 0 26 Aug 2009